Content moderation is an essential yet increasingly complex component of maintaining safe and inclusive online environments. Platforms navigate a growing range of harms, including misinformation, hate speech, harassment, exploitative material, and emerging challenges associated with generative AI and evolving platform...
Robyn Caplan, Stefano Cresci, Catalina Goanta et al.· Proceedings of the 2026 Comp...· 0 citations
Over twenty editions, the ICWSM community has examined social life online as platforms, interactions, and research methods have changed. What can this body of research tell us at this critical juncture, as AI increasingly reshapes how people communicate online? We analyzed 2,139 indexed contributions from 2007 to 2026,...
A randomized vignette experiment with 285 U.S. adults across eight financial decisions independently varying three advice styles---AI, expert, and online community---and displayed source labels while holding the underlying recommendation consistent found expert-style advice remained most preferred when shown without so...
A. Kapadia, Eshwar Chandrasekharan, Koustuv Saha· 0 citations
It was found that both AI summaries and user reviews influenced participants' opinions, with negative summaries having a larger effect than positive ones and negative summaries having a larger effect than positive ones.
Wang Claire, Agam Goyal, Frederick Choi et al.· 0 citations
It is suggested that local preference recognition requires community-specific training signal, not just better prompting, and this work supports future research on community-aware reward modeling, feed curation, and positive moderation.
Agam Goyal, Xianyang Zhan, Charlotte Lambert et al.· 6 citations
It is found that LLMs outperform expectations at replicating comment structure and formality, but struggle to accurately capture nuanced emotions, e.g. understating joy and overstating anger.
Vedaant V. Jain, Yoshee Jain, Ishq Gupta et al.· 0 citations
Findings show that financial-advice evaluations are shaped jointly by displayed attribution and message-level communication cues, which position disclosure not as a neutral transparency mechanism, but as an interpretive frame whose accuracy and interaction with message cues can shape trust and reliance.
A. Kapadia, Eshwar Chandrasekharan, Koustuv Saha· 1 citation
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